A finite mixture modelling perspective for combining experts’ opinions with an application to quantile-based risk measures

Despoina Makariou*, Pauline Barrieu, George Tzougas

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
13 Downloads (Pure)

Abstract

The key purpose of this paper is to present an alternative viewpoint for combining expert opinions based on finite mixture models. Moreover, we consider that the components of the mixture are not necessarily assumed to be from the same parametric family. This approach can enable the agent to make informed decisions about the uncertain quantity of interest in a flexible manner that accounts for multiple sources of heterogeneity involved in the opinions expressed by the experts in terms of the parametric family, the parameters of each component density, and also the mixing weights. Finally, the proposed models are employed for numerically computing quantile-based risk measures in a collective decision-making context.

Original languageEnglish
Article number115
JournalRisks
Volume9
Issue number6
DOIs
Publication statusPublished - 9 Jun 2021

Keywords

  • Expectation maximization algorithm
  • Finite mixture models
  • Opinion pooling
  • Quantile-based risk measures

ASJC Scopus subject areas

  • Accounting
  • Economics, Econometrics and Finance (miscellaneous)
  • Strategy and Management

Fingerprint

Dive into the research topics of 'A finite mixture modelling perspective for combining experts’ opinions with an application to quantile-based risk measures'. Together they form a unique fingerprint.

Cite this